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ROCm 10 通过 llama.cpp 在双 R9700 GPU 上实现 Qwen3.8 27B 模型

一位用户成功配置了 ROCm 10 和 llama.cpp,在双 R9700 GPU 上运行 Qwen3.8 27B 模型。该设置实现了 37-50 tokens/秒 的生成速度,在生成代码时峰值超过 60 tokens/秒,展示了多令牌预测 (MTP) 的有效性。用户注意到与标准的 ROCm Docker 镜像相比,性能有所提升,并确认集成无需复杂的补丁。 AI

影响 展示了开源工具和硬件成功集成以在本地运行大型语言模型。

排序理由 用户成功配置现有软件和硬件以运行特定模型。

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

ROCm 10 通过 llama.cpp 在双 R9700 GPU 上实现 Qwen3.8 27B 模型

本文如何被排名

Signal score
6 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Tool
用户成功配置现有软件和硬件以运行特定模型。
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
infra, model release
Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance
High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
Fresh story with cross-source coverage still developing. Ranking may shift as more sources report.

完整方法见我们的编辑标准

报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/hurdurdur7 ·

    ROCm 10 + llama.cpp + Qwen3.8 27B Q8 K XL with MTP on 2xR9700

    <!-- SC_OFF --><div class="md"><p>TL;DR - yeah it works, no wild skills or patching required.</p> <p>37-50 tg/s when generating text, spiking over 60tg/s when writing code and mtp hits hard. Your results can be better if you have a better motherboard than my aging x370.</p> <p>--…